Question 1

You are building a model to make clothing recommendations. You know a user’s fashion preference is likely to change over time, so you build a data pipeline to stream new data back to the model as it becomes available. How should you use this data to train the model?

Options :

A : Continuously retrain the model on just the new data.

B : Continuously retrain the model on a combination of existing data and the new data.

C : Train on the existing data while using the new data as your test set.

D : Train on the new data while using the existing data as your test set.

Answer: C

Question 2

Your weather app queries a database every 15 minutes to get the current temperature. The frontend is powered by Google App Engine and server millions of users. How should you design the frontend to respond to a database failure?

Options :

A : Issue a command to restart the database servers.

B : Retry the query with exponential backoff, up to a cap of 15 minutes.

C : Retry the query every second until it comes back online to minimize staleness of data.

D : Reduce the query frequency to once every hour until the database comes back online.

Answer: B

Question 3

You need to migrate a 2TB relational database to Google Cloud Platform. You do not have the resources tosignificantly refactor the application that uses this database and cost to operate is of primary concern.Which service do you select for storing and serving your data?

Options :

A : Cloud Spanner

B : Cloud Bigtable

C : Cloud Firestore

D : Cloud SQL

Answer: D

Question 4

You have a BigQuery table that ingests data directly from a Pub/Sub subscription. The ingested data isencrypted with a Google-managed encryption key. You need to meet a new organization policy that requiresyou to use keys from a centralized Cloud Key Management Service (Cloud KMS) project to encrypt data atrest. What should you do?

Options :

A : Create a new BigOuory table by using customer-managed encryption keys (CMEK), and migrate thedata from the old BigQuery table

B : Create a new BigOuery table and Pub/Sub topic by using customer-managed encryption keys (CMEK),and migrate the data from the old Bigauery table.

C : Create a new Pub/Sub topic with CMEK and use the existing BigQuery table by using Google-managedencryption key.

D : Use Cloud KMS encryption key with Dataflow to ingest the existing Pub/Sub subscription to theexisting BigQuery table.

Answer: A

Question 5

You have Cloud Functions written in Node.js that pull messages from Cloud Pub/Sub and send the data to BigQuery. You observe that the message processing rate on the Pub/Sub topic is orders of magnitude higher than anticipated, but there is no error logged in Stackdriver Log Viewer. What are the two most likely causes of this problem? Choose 2 answers.

Options :

A : Publisher throughput quota is too small.

B : Total outstanding messages exceed the 10-MB maximum.

C : Error handling in the subscriber code is not handling run-time errors properly.

D : The subscriber code cannot keep up with the messages.

E : The subscriber code does not acknowledge the messages that it pulls.

Answer: C,D

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